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Background and purpose: In amyotrophic lateral sclerosis (ALS), there is an unmet need for more precise patient characterization through quantitative, ideally operator‐independent, assessments of disease extent and severity. Radially sampled averaged magnetization inversion recovery acquisitions (rAMIRA) magnetic resonance imaging enables gray matter (GM) and white matter (WM) area quantitation in the cervical and thoracic spinal cord (SC) with optimized contrast. We aimed to investigate rAMIRA‐derived SC GM and SC WM areas and their association with clinical phenotype and disability in ALS. Methods: A total of 36 patients with ALS (mean [SD] age 61.7 [12.6] years, 14 women) and 36 healthy, age‐ and sex‐matched controls (HCs; mean [SD] age 63.1 [12.1] years, 14 women) underwent two‐dimensional axial rAMIRA imaging at the inter‐vertebral disc levels C2/3–C5/C6 and the lumbar enlargement level Tmax. ALS Functional Rating Scale–revised (ALSFRS‐R) score, muscle strength, and sniff nasal inspiratory pressure (SNIP) were assessed. Results: Compared to HCs, GM and WM areas were reduced in patients at all cervical levels (p < 0.0001). GM area (p = 0.0001), but not WM area, was reduced at Tmax. Patients with King's Stage 3 showed significant GM atrophy at all levels, while patients with King's Stage 1 showed significant GM atrophy selectively at Tmax. SC GM area was significantly associated with muscle force at corresponding myotomes. GM area at C3/C4 was associated with ALSFRS‐R (p < 0.001) and SNIP (p = 0.0016). Conclusion: Patients with ALS assessed by rAMIRA imaging show significant cervical and thoracic SC GM and SC WM atrophy. SC GM area correlates with muscle strength and clinical disability. GM area reduction at Tmax may be an early disease sign. Longitudinal studies are warranted. [ABSTRACT FROM AUTHOR]

Zhiliang Zhang,1,&ast; Zhongxiang Ding,2,&ast; Fenyang Chen,2 Rui Hua,3 Jiaojiao Wu,3 Zhefan Shen,2 Feng Shi,3 Xiufang Xu1 1School of Medical Imaging, Hangzhou Medical College, Hangzhou, People’s Republic of China; 2Department of Radiology, Affiliated Hangzhou First People’s Hospital, Westlake University School of Medicine, Hangzhou, People’s Republic of China; 3Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Feng Shi; Xiufang Xu, Email feng.shi@uii-ai.com; 1996033011@hmc.edu.cnBackground: Cerebral small vessel disease lacks specific clinical manifestations, and extraction of valuable features from multimodal images is expected to improve its diagnostic accuracy. In this study, we used deep learning techniques to segment cerebral small vessel disease imaging markers in multimodal magnetic resonance images and analyze them with clinical risk factors.Methods and results: We recruited 211 lacunar stroke patients and 83 control patients. The patients’ cerebral small vessel disease markers were automatically segmented using a V-shaped bottleneck network, and the number and volume were calculated after manual correction. The segmentation results of the V-shaped bottleneck network for white matter hyperintensity and recent small subcortical infarction were in high agreement with the ground truth (DSC> 0.90). In small lesion segmentation, cerebral microbleed (average recall=0.778; average precision=0.758) and perivascular spaces (average recall=0.953; average precision=0.923) were superior to lacunar infarct (average recall=0.339; average precision=0.432) in recall and precision. Binary logistic regression analysis showed that age, systolic blood pressure, and total cerebral small vessel disease load score were independent risk factors for lacunar stroke (P< 0.05). Ordered logistic regression analysis showed age was positively correlated with cerebral small vessel disease load score and total cholesterol was negatively correlated with cerebral small vessel disease score (P< 0.05).Conclusion: Lacunar stroke patients exhibited higher cerebral small vessel disease imaging markers, and age, systolic blood pressure, and total cerebral small vessel disease score were independent risk factors for lacunar stroke patients. V-shaped bottleneck network segmentation network based on multimodal deep learning can segment and quantify various cerebral small vessel disease lesions to some extent.Keywords: lacunar stroke, cerebral small vessel disease, imaging markers, deep learning, quantification, image segmentation, clinical risk factors

A comprehensive evaluation of cardiac function includes information in relation to cardiac output and systemic venous return. The heart is composed of four chambers: two atria and two ventricles, each with its own unique mechanical function. These four cardiac chambers, their valves, and the pulmonary circulation system are inter-related as they preload or afterload on each other. Cardiac dysfunction is a failure of global cardiac function, resulting in typical clinical manifestations. To investigate the underlying cause of cardiac dysfunction, a step-by-step evaluation of cardiac blood flow tracks is necessary. In this context, imaging markers showing details of the cardiac structures have an important role in assessing cardiac function. An image- based evaluation allows for investigation of function in terms of individual cardiac components. Evaluation of cardiac function using cardiac CT has recently been validated. This review aimed to discuss cardiac CT-based imaging markers for comprehensive and detailed cardiac function assessment.

A comprehensive evaluation of cardiac function includes information in relation to cardiac output and systemic venous return. The heart is composed of four chambers: two atria and two ventricles, each with its own unique mechanical function. These four cardiac chambers, their valves, and the pulmonary circulation system are inter-related as they preload or afterload on each other. Cardiac dysfunction is a failure of global cardiac function, resulting in typical clinical manifestations. To investigate the underlying cause of cardiac dysfunction, a step-by-step evaluation of cardiac blood flow tracks is necessary. In this context, imaging markers showing details of the cardiac structures have an important role in assessing cardiac function. An image-based evaluation allows for investigation of function in terms of individual cardiac components. Evaluation of cardiac function using cardiac CT has recently been validated. This review aimed to discuss cardiac CT-based imaging markers for comprehensive and detailed cardiac function assessment. [ABSTRACT FROM AUTHOR]

Background Hemodynamic stress is linked to the development of intracranial aneurysms (IAs) and may be influenced by anatomic variation of intracranial arteries. We assessed diameters and bifurcation angles of intracranial arteries forming the circle of Willis in a cohort of individuals screened for the presence of IAs. Methods Individuals with and without IAs identified at screening with magnetic resonance angiography were compared. Diameters and bifurcation angles of the following arteries were measured using semiautomatic methods: A1 and A2 segments of the anterior cerebral artery, M1 and M2 segments of the middle cerebral artery, P1 segments of the posterior cerebral artery, posterior communicating artery (Pcom), internal carotid artery, vertebral artery, and basilar artery. We employed univariate general linear models to assess group differences. This included subgroup comparisons between individuals with IAs at specific locations and matched controls, and comparisons on group level between individuals with and without IAs, corrected for age and sex. Results In 94 of the 1049 individuals (9.0%) included, IAs were detected. Individuals with middle cerebral artery IAs had wider ipsilateral M2–M2 bifurcation angles compared with controls (121±25° versus 97±19°; P

Background: Cerebral edema is a secondary complication of acute ischemic stroke, but its time course and imaging markers are not fully understood. Recently, net water uptake (NWU) has been proposed as a novel marker of edema. Aims: Studying the RHAPSODY trial cohort, we sought to characterize the time course of edema and test the hypothesis that NWU provides distinct information when added to traditional markers of cerebral edema after stroke by examining its association with other markers. Methods: A total of 65 patients had measurable supratentorial ischemic lesions. Patients underwent head computed tomography (CT), brain magnetic resonance imaging (MRI) scans, or both at the baseline visit and after 2, 7, 30, and 90 days following enrollment. CT and MRI scans were used to measure four imaging markers of edema: midline shift (MLS), hemisphere volume ratio (HVR), cerebrospinal fluid (CSF) volume, and NWU using semi-quantitative threshold analysis. Trajectories of the markers were summarized, as available. Correlations of the markers of edema were computed and the markers compared by clinical outcome. Regression models were used to examine the effect of 3K3A-activated protein C (APC) treatment. Results: Two measures of mass effect, MLS and HVR, could be measured on all imaging modalities, and had values available across all time points. Accordingly, mass effect reached a maximum level by day 7, normalized by day 30, and then reversed by day 90 for both measures. In the first 2 days after stroke, the change in CSF volume was associated with MLS (ρ = –0.57, p = 0.0001) and HVR (ρ = –0.66, p < 0.0001). In contrast, the change in NWU was not associated with the other imaging markers (all p ⩾ 0.49). While being directionally consistent, we did not observe a difference in the edema markers by clinical outcome. In addition, baseline stroke volume was associated with all markers (MLS (p < 0.001), HVR (p < 0.001), change in CSF volume (p = 0.003)) with the exception of NWU (p = 0.5). Exploratory analysis did not reveal a difference in cerebral edema markers by treatment arm. Conclusions: Existing cerebral edema imaging markers potentially describe two distinct processes, including lesional water concentration (i.e. NWU) and mass effect (MLS, HVR, and CSF volume). These two types of imaging markers may represent distinct aspects of cerebral edema, which could be useful for future trials targeting this process. [ABSTRACT FROM AUTHOR]

• There is moderate correlation between upper extremity lean tissue mass as measured by DEXA scans and their corresponding strengths measured by quantitative muscle testing. • There is moderate correlation between lower extremity lean tissue mass and corresponding strength measured by quantitative muscle testing and manual muscle testing. • There is moderate correlation between bilateral lower extremity lean tissue mass and 6-minute walk test, 10-meter walk/run, and timed-up-and-go. Facioscapulohumeral muscular dystrophy (FSHD) is a slowly progressive disease of skeletal muscle. Dual energy X-ray absorptiometry (DEXA) is a widely available, cost-effective and sensitive technique for measuring whole body and regional lean tissue mass and has been used in prior clinical trials in neuromuscular diseases. The Clinical Trial Readiness to Solve Barriers to Drug Development in FSHD (ReSolve) study is a prospective, longitudinal, observational multisite study. We obtained concurrent DEXA scans and functional outcome measurements in 185 patients with FSHD at the baseline visit. We determined the associations between lean tissue mass in the upper and lower extremities and corresponding clinical outcome measures. There were moderate correlations between upper and lower extremity lean tissue mass and their corresponding strengths and function. Lean tissue mass obtained by DEXA scan may be useful as a biomarker in future clinical trials in FSHD. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a complex neurodegenerative disorder characterized by motor symptoms such as bradykinesia, rigidity, and resting tremor. While the majority of PD cases are sporadic, approximately 15–20% of cases have a genetic component. Advances in neuroimaging techniques have provided valuable insights into the pathophysiology of PD, including the different genetic forms of the disease. This literature review aims to summarize the current state of knowledge regarding neuroimaging findings in genetic PD, focusing on the most prevalent known genetic forms: mutations in the GBA1, LRRK2, and Parkin genes. In this review, we will highlight the contributions of various neuroimaging modalities, including positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI), in elucidating the underlying pathophysiological mechanisms and potentially identifying candidate biomarkers for genetic forms of PD. [ABSTRACT FROM AUTHOR]

Introduction: Stroke is a major global health concern and is ranked as the second leading cause of death worldwide, with the third highest incidence of disability. Intracerebral hemorrhage (ICH) is a devastating form of stroke that is responsible for a significant proportion of stroke-related morbidity and mortality worldwide. Hematoma expansion (HE), which occurs in up to one-third of ICH patients, is a strong predictor of poor prognosis and can be potentially preventable if high-risk patients are identified early. In this review, we provide a comprehensive summary of previous research in this area and highlight the potential use of imaging markers for future research studies. Recent advances: Imaging markers have been developed in recent years to aid in the early detection of HE and guide clinical decision-making. These markers have been found to be effective in predicting HE in ICH patients and include specific manifestations on Computed Tomography (CT) and CT Angiography (CTA), such as the spot sign, leakage sign, spot-tail sign, island sign, satellite sign, iodine sign, blend sign, swirl sign, black hole sign, and hypodensities. The use of imaging markers holds great promise for improving the management and outcomes of ICH patients. Conclusion: The management of ICH presents a significant challenge, and identifying high-risk patients for HE is crucial to improving outcomes. The use of imaging markers for HE prediction can aid in the rapid identification of such patients and may serve as potential targets for anti-HE therapies in the acute phase of ICH. Therefore, further research is needed to establish the reliability and validity of these markers in identifying high-risk patients and guiding appropriate treatment decisions. [ABSTRACT FROM AUTHOR]

Summary: Heart failure with preserved ejection fraction is an increasing challenge for modern day medicine and has been drawing more attention recently. Invasive right heart catheterization represents the mainstay for the diagnosis of diastolic dysfunction, however due to its attributable risk of an invasive procedure, other non-invasive clinical pathways are trying to approach this pathology in clinical practice. Diastolic failure is complex, and imaging is based on various parameters. In addition to transthoracic echocardiography, numerous novel imaging approaches, such as cardiac magnetic resonance imaging, computed tomography, positron emission (computed) tomography or single photon emission tomography techniques are being used to supplement deeper insights into causal pathology and might open targets for dedicated therapy options. This article provides insights into these sophisticated imaging techniques, their incremental value for the diagnosis of this poorly understood disease and recent promising results for an enhanced prognostication of outcome and therapy monitoring.

Neuromyelitis optica spectrum disorder (NMOSD) is a rare inflammatory demyelinating disorder of the central nervous system (CNS). Aquaporin-4 (AQP4) antibodies in the serum are highly specific for the diagnosis of NMOSD, but the sensitivity remains under 90% allowing for diagnosis of AQP4 IgG seronegative disease. It remains of crucial importance to identify seronegative NMOSD myelitis as early as the first attack to initiate long-term treatment that will reduce future relapses and disability and to avoid potentially harmful treatments such as those of multiple sclerosis (MS). Over the years, many spinal imaging features have been reported to favour the diagnosis of NMOSD, but only longitudinally extensive transverse myelitis (LETM) was specific enough to make the diagnostic criteria in the AQP4 IgG seronegative cases. Bright spotty lesions (BSLs), which are defined as hyperintense lesions on axial T2-weighted images and sometimes associated with T1 low signal, are now reported to have a higher specificity and sensitivity compared to LETM in predicting a diagnosis of NMOSD against other causes of myelitis. In the review, we aim to highlight the position of BSLs in diagnosing NMOSD as well as its possible role as a prognostic factor for the clinical outcome. [ABSTRACT FROM AUTHOR]

Purpose: Vessel wall MRI (VW-MRI) can be used to evaluate the nature of intracranial atherosclerosis (ICAS) plaque in vivo. Phosphodiesterase 4D (PDE4D) participates in stroke development. This study aims to explore the value of VW-MRI findings and the PDE4D gene variant in predicting stroke recurrence in patients with ICAS. Methods: We prospectively recruited 324 symptomatic ICAS patients. VW-MRI was performed to determine luminal and wall changes. PDE4D gene single-nucleotide polymorphisms (SNPs)—namely, SNP32, SNP83, and SNP87—were determined by direct sequencing. The risk factors of stroke recurrence were analyzed using the multivariate Cox proportional hazards model. Results: Of the 324 subjects, 97 (29.9%) experienced recurrent ischemic stroke during the follow-up period. A total of 254 patients (78.4%) showed plaque enhancement; 87 of these patients experienced stroke recurrence. The CT/CC genotype frequencies of PDE4D83 were significantly higher in participants with recurrent stroke than in patients without stroke recurrence (p = 0.019 and p < 0.001, respectively). However, the PDE4D32 and PDE4D87 variants were not correlated with recurrent stroke. Multivariate analysis showed that plaque enhancement from VW-MRI (HR 4.52, 95% CI 2.35–8.73, p < 0.001) and the PDE4D83 variant (HR 7.43, 95% CI 1.75–31.87, p = 0.005) were independently correlated with stroke recurrence. Kaplan–Meier curves showed significant differences in stroke recurrence rates between the plaque-enhanced group and the non-enhanced group (p < 0.001) and between the PDE4D83 variant carriers and noncarriers (p = 0.002). Conclusion: Plaque enhancement on VW-MRI and the presence of the PDE4D83 variant are associated with ischemic stroke recurrence in subjects with symptomatic ICAS. [ABSTRACT FROM AUTHOR]

Background: The association between imaging features closely associated with symptomatic intracranial atherosclerotic plaques and early-onset post-stroke depression (PSD) is currently unclear.Materials and Methods: 76 ischemic stroke patients who underwent high-resolution vessel wall magnetic resonance imaging (HR-VWI) were divided into PSD and non-PSD groups according to their DSM-V diagnoses and HAMD-17 scores at 14 days after onset. Clinical data and the imaging features associated with symptomatic plaques (including the enhancement index (EI), remodeling index, and plaque surface irregularity) were compared between groups. Multifactorial logistic regression analysis was used to find independent predictors of early-onset PSD. Spearman rank correlation analysis explores the association between clinical data, symptomatic plaque imaging features, and HAMD-17 in patients.Results: The sample comprised 36 patients with early-onset PSD. The symptomatic plaque EI and infarct volume were significantly higher in depressed patients than in patients without depression (P < 0.05). Multivariate logistic regression showed that symptomatic plaque EI could be used as an independent predictor of early-onset PSD after correcting for the confounding factor of infarct volume (OR = 1.034, 95% CI:1.014-1.055, P = 0.001). In the total sample, symptomatic plaque EI, infarct volume, and HAMD-17 had a significant positive correlation with each other (P < 0.05).Limitations: This study focused only on the patients' symptomatic plaques and did not monitor patients' systemic inflammation levels at the time of HR-VWI.Conclusions: The degree of symptomatic plaque enhancement is an independent predictive imaging marker of early-onset PSD and can be used the early diagnosis of early-onset PSD. [ABSTRACT FROM AUTHOR]

Currently, various methods for inspecting ischemic stroke are available, especially the imaging techniques, which play an important role in assisting diagnosis and prognostication of ischemic stroke. In the acute phase of ischemic stroke, however, there still lack of well-established imaging markers that could reliably predict patients’ functional outcome. We thus reviewed literatures focusing on relevant imaging markers of ischemic tissue, intra-arterial thrombus, arterial collateral circulation, draining veins and functional connectivity, which may be valuable to evaluate the initial severity of stroke in the acute phase of ischemic stroke and predict neurological outcome in the long term.

Purpose: Probe-based dynamic (4-D) imaging modalities capture breast intratumor heterogeneity both spatially and kinetically. Characterizing heterogeneity through tumor sub-populations with distinct functional behavior may elucidate tumor biology to improve targeted therapy specificity and enable precision clinical decision making. Methods: We propose an unsupervised clustering algorithm for 4-D imaging that integrates Markov-Random Field (MRF) image segmentation with time-series analysis to characterize kinetic intratumor heterogeneity. We applied this to dynamic FDG PET scans by identifying distinct time-activity curve (TAC) profiles with spatial proximity constraints. We first evaluated algorithm performance using simulated dynamic data. We then applied our algorithm to a dataset of 50 women with locally advanced breast cancer imaged by dynamic FDG PET prior to treatment and followed to monitor for disease recurrence. A functional tumor heterogeneity (FTH) signature was then extracted from functionally distinct sub-regions within each tumor. Cross-validated time-to-event analysis was performed to assess the prognostic value of FTH signatures compared to established histopathological and kinetic prognostic markers. Results: Adding FTH signatures to a baseline model of known predictors of disease recurrence and established FDG PET uptake and kinetic markers improved the concordance statistic (C-statistic) from 0.59 to 0.74 (p = 0.005). Unsupervised hierarchical clustering of the FTH signatures identified two significant (p < 0.001) phenotypes of tumor heterogeneity corresponding to high and low FTH. Distributions of FDG flux, or Ki, were significantly different (p = 0.04) across the two phenotypes. Conclusions: Our findings suggest that imaging markers of FTH add independent value beyond standard PET imaging metrics in predicting recurrence-free survival in breast cancer and thus merit further study. [ABSTRACT FROM AUTHOR]

With the ongoing advances in imaging techniques, increasing volumes of anatomical and functional data are being generated as part of the routine clinical workflow. This surge of available imaging data coincides with increasing research in quantitative imaging, particularly in the domain of imaging features. An important and novel approach is radiomics, where high-dimensional image properties are extracted from routine medical images. The fundamental principle of radiomics is the hypothesis that biomedical images contain predictive information, not discernible to the human eye, that can be mined through quantitative image analysis. In this review, a general outline of radiomics and artificial intelligence (AI) will be provided, along with prominent use cases in immunotherapy (e.g. response and adverse event prediction) and targeted therapy (i.e. radiogenomics). While the increased use and development of radiomics and AI in immuno-oncology is highly promising, the technology is still in its early stages, and different challenges still need to be overcome. Nevertheless, novel AI algorithms are being constructed with an ever-increasing scope of applications.

Background: The cognitive trajectories in normal aging may be affected by medial temporal atrophy (MTA) and amyloid burden, as well as vascular pathologies such as cortical microbleeds (CMB) and white matter hyperintensities (WMH).Objective: We addressed here the role of imaging markers in their prediction in a real-world situation.Methods: We performed a 4.5-year longitudinal study in 90 older community-dwellers coupling two neuropsychological assessments, MTA estimated with the Schelten's scale, number of CMB, and WMH evaluated with the Fazekas score at inclusion and follow-up, visual rating of amyloid PET and glucose hypometabolism at follow-up, and APOE genotyping. Regression models were built to explore the association between the continuous cognitive score (CCS) and imaging parameters.Results: The number of strictly lobar CMB at baseline (4 or more) was related to a 5.5-fold increase of the risk of cognitive decrement. This association persisted in multivariable models explaining 10.6% of the CCS decrease variance. MTA, and Fazekas score at baseline and amyloid positivity or abnormal FDG PET, were not related to the cognitive outcome. The increase of right MTA at follow-up was the only correlate of CCS decrease both in univariate and multivariable models explaining 9.2% of its variance.Conclusion: The present data show that the accumulation of more than four CMB is associated with significant cognitive decrement over time in highly educated elderly persons. They also reveal that the progressive deterioration of cognitive performance within the age-adjusted norms is also related to the increase of visually assessed MTA. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the association between plaque enhancement and stroke recurrence in subjects with intracranial atherosclerosis. Methods: Ischemic stroke patients with symptomatic intracranial atherosclerosis were prospectively included and followed in a comprehensive stroke center. Pre- and post-contrast vessel wall images were used to evaluate plaque enhancement. Other established suggestive imaging markers were also acquired simultaneously. Univariate- and multivariate-adjusted Cox proportional hazard regression models were used to determine the association between plaque enhancement and stroke recurrence. Finally, receiver operating characteristic (ROC) curves were used to demonstrate the predictive value of different imaging markers. Results: Of the 60 subjects included, 12 (20.0%) patients presented with ipsilateral stroke recurrence during the median 12-month follow-up. Cox proportional hazard regression models indicated that plaque enhancement was an independent risk factor associated with stroke recurrence after adjusted covariates, with a hazard ratio (HR) of 14.24 and 95% confidence interval (95% CI) (1.21, 168.11), p = 0.04. In addition, border zone infarction was also statistically significant in predicting stroke recurrence in multi-variable regression (HR = 3.80; 95% CI = 1.04, 13.80; p = 0.04). Collateral status was in marginal significance (HR = 0.25; 95% CI = 0.06, 1.08; p = 0.06). ROC analysis indicated that the area under the curve and 95% CI to identify stroke recurrence are 0.67 (0.51, 0.82) for plaque enhancement and 0.71 (0.54, 0.88) for infarction pattern and collateral status and may increase to 0.82 (0.70, 0.93) by combining the three markers above. Conclusion: Plaque enhancement is independently associated with stroke recurrence in subjects with intracranial atherosclerosis and has added value to hemodynamic indicators in predicting stroke recurrence. [ABSTRACT FROM AUTHOR]

To establish a new nomogram model and provide a new theoretical basis for the diagnosis and treatment of spontaneous intracerebral hemorrhage. The clinical data and noncontrast computed tomography images of patients with spontaneous intracerebral hemorrhage in 3 tertiary medical centers were collected continuously. Univariate and binary logistic regression analysis were performed to screen out the independent predictors that were significantly associated with hematoma expansion. The nomogram model was drawn by R programming language. According to the related risk factors of nomogram, decision curve analysis and clinical impact curve were established. The numbers of the 3 cooperative units were 554, 582, and 202, respectively. Island sign, blend sign, swirl sign, intraventricular hemorrhage, history of diabetes, time to baseline computed tomography scan, and baseline hematoma volume were independent predictors of hematoma expansion. Baseline hematoma volume >20 mL (odds ratio, 4.088; 95% confidence interval, 2.802–5.964; P < 0.0001) was the most dangerous factor for predicting hematoma expansion, followed by the time to baseline computed tomography scan ≤1 hour (odds ratio, 4.188; 95% confidence interval, 2.598–6.750; P < 0.0001). Decision curve analysis showed that the net benefit of patients was the highest when nomogram score existed. When the threshold probability was >40%, the prediction probability of hematoma expansion was close to the actual probability. This nomogram model could accurately predict hematoma expansion of spontaneous intracerebral hemorrhage, which provided a theoretical basis for clinicians to intervene in the early stage. [ABSTRACT FROM AUTHOR]

Background and Objective Intracerebral hemorrhage (ICH) is the most difficult-to-treat form of stroke and accounts for about 10%–30% of all strokes worldwide. Hematoma expansion (HE), which occurs in one third of patients with ICH, is strongly predictive of worse prognosis and potentially preventable if high-risk patients are identified in the early phase of ICH. We summarized data from recent studies on HE prediction and classified those potential indicators into 2 categories: 1) clinical and laboratory and 2) radiographic. Therefore, we aimed to identify the accuracy of L, that is, the value of combining predictors in predicting HE of ICH in basal ganglia. Methods We retrospectively investigated the clinical database of Qinghai Provincial People's Hospital for patients with ICH aged >18 years between January 2015 and January 2018. As inclusion criteria, we defined 1) ICH diagnosed on noncontrast computed tomography (CT); 2) noncontrast CT performed on enrollment within 6 hours after onset of symptoms; 3) follow-up CT scan performed within 24 hours after the baseline CT scan; and 4) all of the primary hematoma was located in the basal ganglia. Univariate and multivariate logistic regression analysis were used to analyze the potential HE predictors, and then receiver operating characteristic curves were used to evaluate the L (the value of combining predictors) of imaging markers and clinical factors in predicting HE. Results Of the 99 patients with HE, island sign was present in 48.48% (48/99) of patients and blend sign was present in 34.34% (34/99) of patients. Multivariate logistic regression analysis identified time to baseline CT scan (odds ratio [OR] 1.574; 95% confidence interval [CI] 1.205–2.054; P = 0.001), baseline hematoma volume (P = 0.001), presence of island sign (OR 11.247; 95% CI 4.701–26.909; P = 0.000), presence of blend sign (OR 3.104; 95% CI 1.425–6.765; P = 0.004), anticoagulants use or international normalized ratio >1.5 (OR 2.755; 95% CI 1.072–7.082; P = 0.035), and intraventricular hemorrhage (OR 2.351; 95% CI 1.066–5.187; P = 0.034) as independent predictors of HE. The sensitivity and specificity of L (value of combining predictors) were 88.89% and 80.84%, respectively; the area under the curve was 0.918. Conclusions The findings indicated that the ability of L to predict HE was much more excellent than these 6 predictors alone. L showed a high association with HE, with an accuracy of 91.8%, and was a reliable value of combining predictors in terms of predicting HE. L may serve as a promising, noninvasive tool for clinical therapeutic strategy. Highlights • This is the first study to use value of combining predictors (L) to predict HE in patients with ICH. • It is also the first study to combine imaging markers (island sign and blend sign) and clinical factors to predict HE. • ROC curve analysis showed that the ability of L to predict HE was much more excellent than these 6 predictors alone. • L showed a high association with HE (accuracy of 91.8%) and was a reliable value of combining predictors to predict HE. • L may serve as a promising, noninvasive tool for clinical therapeutic strategy. [ABSTRACT FROM AUTHOR]

Background: Hematoma expansion is an independent risk factor of unfavorable outcome after intracerebral hemorrhage (ICH), which always occurs in the early phase after symptoms onset. The relationship between underlying small vessel disease (SVD) and hematoma expansion was inconsistent in patients with ICH. We aimed to investigate the relationship between magnetic resonance (MR) characteristics of SVD and hematoma expansion in patients with ICH within 72 hours after symptoms onset.Methods: Data were derived from a cohort of biological sample collection from April 2014 to April 2016. We recruited patients aged 18 years or older with a baseline and follow-up computed tomography within 72 hours after symptom onset, as well as an MR imaging within 3 months before or after ICH. Hematoma expansion was defined as an increase in volume between baseline and final hematoma volume exceeding 6 mL or 33% of the baseline volume. Multivariate logistic regression was used to explore the association between clinical characteristics, imaging markers, total SVD score, and hematoma expansion in patients with ICH.Results: A total of 103 patients experienced hematoma expansion among the 263 enrolled patients (mean age 53.4 ± 14.0 years, 76.4% male). Electrocardiogram abnormal rhythm, fewer non-lobar microbleeds, lower plasma homocysteine concentration, and smaller baseline hematoma volume independently predicted the risk of hematoma expansion (P = .004, .021, .001, and .024, respectively). Odds ratios ranged from 1.02 to 3.72.Conclusions: Our study suggested that the use of MR markers revealing underlying SVD may help to identify patients with ICH with potential hematoma expansion. [ABSTRACT FROM AUTHOR]

The clinical relevance of gray/white matter contrast ratio (GWR) in mild cognitive impairment (MCI) remains unknown. This study examined baseline GWR and 3-year follow-up diagnostic status in MCI. Alzheimer's Disease Neuroimaging Initiative MCI participants with baseline 1.5 T MRI and 3-year follow-up clinical data were included. Participants were categorized into two groups based on 3-year follow-up diagnoses: 1) non-converters ( n = 69, 75 ± 7, 26 % female), and 2) converters (i.e., dementia at follow-up; n = 69, 75 ± 7, 30 % female) who were matched on baseline age and Mini-Mental State Examination scores. Groups were compared on FreeSurfer generated baseline GWR from structural images in which higher values represent greater tissue contrast. A general linear model, adjusting for APOE-status, scanner type, hippocampal volume, and cortical thickness, revealed that converters evidenced lower GWR values than non-converters (i.e., more degradation in tissue contrast; p = 0.03). Individuals with MCI who convert to dementia have lower baseline GWR values than individuals who remain diagnostically stable over a 3-year period, statistically independent of cortical thickness or hippocampal volume. [ABSTRACT FROM AUTHOR]

Alzheimer’s disease (AD) is the most common neurodegenerative disorder in elderly people, but there are still no curative options. Senile plaques and neurofibrillary tangles are considered hallmarks of AD, but cerebrovascular pathology is also common. In this review, we summarize findings on cardiovascular disease (CVD) and risk factors in the etiology of AD. Firstly, we discuss the association of clinical CVD (such as stroke and heart disease) and AD. Secondly, we summarize the relation between imaging makers of pre-clinical vascular disease and AD. Lastly, we discuss the association of cardiovascular risk factors and AD. We discuss both established cardiovascular risk factors and emerging putative risk factors, which exert their effect partly via CVD. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms and the time and spatial evolution of penumbra following an ischemic stroke is crucially important for developing therapeutics aimed at preventing this area from evolving towards infarction. To help in integrating the available data, we decided to build a formal model. We first collected and categorised the major available evidence from animal models and human observations and summarized this knowledge in a flow-chart with the potential key components of an evolving stroke. Components were grouped in ten sub-models that could be modelled and tested independently: the sub-models of tissue reactions, ionic movements, oedema development, glutamate excitotoxicity, spreading depression, NO synthesis, inflammation, necrosis, apoptosis, and reperfusion. Then, we figured out markers, identified mediators and chose the level of complexity to model these sub-models. We first applied this integrative approach to build a model based on cytotoxic oedema development following a stroke. Although this model includes only three sub-models and would need to integrate more mechanisms in each of these sub-models, the characteristics and the time and spatial evolution of penumbra obtained by simulation are qualitatively and, to some extent, quantitatively consistent with those observed using medical imaging after a permanent occlusion or after an occlusion followed by a reperfusion. [ABSTRACT FROM AUTHOR]

Acute ischemic stroke treatment has been revolutionized by the addition of mechanical and aspiration thrombectomy. Randomized controlled trials have proven beyond doubt, the substantial clinical impact of endovascular interventions in anterior circulation territory strokes. Unfortunately, patients with vertebrobasilar ischemic stroke could not be included in these early trials due to inherent clinical, radiological, and prognostic particularities of posterior circulation ischemia; thus, indications for the treatment of posterior fossa strokes and basilar artery occlusion (BAO) are mainly based on retrospective studies and registries. BAO carries high morbidity and mortality, despite the new improvements in endovascular therapy. Identifying patients who will likely benefit from invasive treatment and have a good clinical outcome resides in discovering clinical, biological, or imaging markers, that have prognostic implications. Such imaging markers have been described, especially in the last decade. Hyperdense Basilar Artery Sign (HDBA), Posterior Circulations-Alberta Stroke Program Early CT Score (pc-ASPECTS), Pons-Midbrain Index (PMI), Posterior Circulation Collateral Score (pc-CS), Posterior Circulation CT Angiography Score (pc-CTA), and Basilar Artery on CT Prognostic Score (BATMAN), are computed tomography (CT) markers with properties that can aid the diagnosis of BAO and can independently predict clinical outcome. This paper aims to present a comprehensive review of these imaging signs to have a thorough understanding of their diagnostic and prognostic attributes. [ABSTRACT FROM AUTHOR]